Dynamic Reporting

Schedule

1. What is dynamic reporting?

2. How to do dynamic reporting?

3. Hands-on exercises

Manual reporting workflow

What are the disadvantages?

Dynamic reporting workflow

Popular tools for dynamic reporting

• R Markdown
• knitr
• Quarto
• (Jupyter Notebooks)

R Markdown

• R programming language
  (> 60 other also possible)

• .Rmd files

• Markdown text markup language

• HTML, PDF, DOCX output formats (and more)

• rmarkdown is an R package

knitr

• Programming language: R
  (> 60 other also possible)

• .Rnw files

• Markup languages: LaTeX
  (+ HTML, Markdown, and more)

• HTML, PDF, DOCX output formats (and more)

• knitr is an R package

Quarto

• Programming language: R, Python, Julia

• .qmd files

• Markup language: Markdown

• HTML, PDF, DOCX output formats (and more)

• Evolution of R Markdown

• quarto is a separate program

Which tool for whom?

• rmarkdown → R users (beginner to advanced)
• knitr → R+LaTeX users (intermediate to advanced)
• quarto → R/Python/Julia users (beginner to advanced)

Useful links

• Dynamic Reporting & Reproducibility in Research
  → transdisciplinary course at UZH

• R Markdown tutorial
  → good tutorial series from R Studio

• R Markdown: The Definitive Guide
  → freely available book

• knitr website
  → very comprehensive website from the knitr author

• Quarto tutorial
  → good tutorial series from R Studio

Exercises

1. Download the data sets from https://github.crsuzh/dynamicReporting/XXXXX

2. Produce a dynamic report with the tool of your choice. Use the data from 2020 to compute …. Make a chart of …. Automate

3. Now use the data from 2020 and 2021 and rerun your analysis